Knowledge-based and collaborative-filtering recommender systems facilitate electronic commerce by helping users find appropriate products from large catalogs. This paper discusses the strengths and weaknesses of both techniques and introduces the possibility of a hybrid recommender system that combines the two approaches. An approach is suggested in which knowledge-based techniques are used to bootstrap the collaborative filtering engine while its data pool is small, and the collaborative filter is used as a post-filter for the knowledge-based recommender.

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